1. Field of the Invention
This invention relates to apparatus and methods for organizing data at levels of granularity that are larger or smaller than an extent.
2. Background of the Invention
In today's tiered storage architectures, the “hotness” or “coldness” of data may be continually monitored so that it can be optimally placed on storage media. For example, “hot” (i.e., frequently accessed) data may be placed on faster, more expensive storage media (e.g., solid state drives) to improve I/O performance. “Cold” (i.e., less frequently accessed) data may be placed on slower, less expensive storage media (e.g., hard disk drives) with reduced I/O performance. As the temperature of the data changes, the data may be migrated between storage tiers to optimize I/O performance.
In some tiered storage architectures, data is migrated between tiers at the granularity of an extent. For example, the IBM DS8000™ storage system moves data between tiers in one GB extents. Unfortunately, the granularity of extents may differ significantly from the granularity of data at the application or higher layers. For example, an application may manage data in the form of files or datasets, which may be considerably smaller or larger than extents. Like the temperature of extents, the “hotness” and “coldness” of files or datasets may differ from one another. Because a storage system may be unaware of data organization at the application layer, data may be organized in an inefficient manner on the underlying storage media. For example, because a single extent may contain both “hot” and “cold” datasets, moving the extent to faster storage media will move not only the “hot” datasets to the faster storage media, but also the “cold” datasets, resulting in less than optimal data organization and poor utilization on the underlying storage media.
In view of the foregoing, what are needed are apparatus and methods to more optimally organize data in tiered storage architectures. Ideally, such apparatus and methods will enable storage systems to organize data at levels of granularity that are larger or smaller than an extent.